Individual and Social Perspectives of Business Intelligence Systems: User Intention in Saudi’s SMEs

Globally, decision makers in companies have been attracted by Business Intelligence Systems (BISs) for their high ability in forecasting the current and future views of the decision process in business operations. Surely, the impacts of BIS will be realized when these systems are used intensively. Based on the literature, more than 70% of BIS projects fail to achieve their expected returns and benefits. Review of literature shows there is dearth of research surrounding BIS acceptance in SMEs especially in developing countries such as Saudi Arabia (SA). This study extends the current literature of users’ post-adoption behaviour of BISs by proposing model that integrates individual and social perspective factors as effective factors in BIS user behaviour intention in Saudi’s SMEs. BIS and SME characteristics have been considered in the implementation of this model. This study seeks to address the gap in the literature and provide better understanding of BIS post-adopt behaviour in SMEs

Revisión sistemática del estado del arte de la Inteligencia de Negocios en el periodo 2016-2020

Este artículo tiene por objetivo realizar una revisión sistemática sobre la inteligencia de negocios entre los años 2016-2020, para lo cual se analiza un conjunto de artículos científicos referentes a los avances que se han producido en dicho período, se discute el impacto que ha tenido la adopción de la inteligencia de negocios en su estrategia corporativa como clave del éxito y el logro de ventajas competitivas considerables a lo largo de los cuatro años. Para este trabajo se emplea un método de mapeo sistemático basado en un modelo de tres bloques: Definiciones de Protocolo, Ejecución de Búsqueda, Discusión de Resultados. Finalmente se presenta los resultados, hallazgos y se describe la relevancia que ha tenido la inteligencia de negocios en el período 2016-2020.This article aims to conduct a systematic review on business intelligence between 2016-2020, for which a set of scientific articles concerning the advances that have occurred in that period is analyzed, the impact that has had the adoption of business intelligence in its corporate strategy as a key to success, achieving considerable competitive advantages over the four years will be discussed. For this work, a systematic mapping method based on the three-block model is used: Protocol Definitions, Search Execution, Results Discussion. Finally, the results and findings are presented describing the relevance of business intelligence in the period 2016- 2020

BUSINESS INTELLIGENCE CAPABILITIES' EFFECTS ON PERFORMANCE IN A COMPETITIVE ENVIRONMENT STUDYING ON-SITE AT THE TOUCHES FOUNDATION FOR ART AND INNOVATION

Abstract This study aims to determine how the touches Foundation for Innovation and the Arts' competitive performance was impacted by its business intelligence capabilities. All 63 members of the touches Foundation for Innovation and the Arts make up the study community. The study's methodology was based on a scoring descriptive approach that identified two aspects-the first of which was business intelligence capabilities-and three other dimensions. These are (business intelligence techniques, business intelligence structure, and business intelligence culture) and competitive performance after four dimensions (cost, quality, flexibility. access) According to the study's findings, the Touches Foundation for Innovation and the Arts employees had an average degree of business intelligence across all of its aspects. The study's findings also indicated that the Touches Foundation for Innovation and the Arts employees' level of performance in a competitive environment was average additionally, the findings of the regression equation have demonstrated that there are statistically significant disparities between competitive performance and business intelligence skills across all dimensions. The study's conclusion included a number of recommendations, including educating the company's leadership and workers about the importance of acquiring business intelligence skills in order to enhance the operation of the company and take advantage of future business prospects

Determinants of stamps assessment and payment system (stamps) online payment usage among Kuala Lumpur branch duty payers

Stamps Assessment and Payment System (STAMPS) service is one of online service offered by Inland Revenue Board of Malaysia (IRBM) to duty payers who have STAMPS ID. This system enables duty payers to check stamp duty assessment and payment transaction records via internet. However, the number of user’s payment is still low compare to the number of STAMPS users. This study attempts to identify the determinants of STAMPS online payment usage among Kuala Lumpur Branch duty payers. The research design adopted the Diffusion of Innovations (DOI) Theory. Data were collected from 86 duty payers who attended the stamp duty counter of Kuala Lumpur Branch using a wellstructured questionnaire. Regression analysis was used to identify the influence of duty payer construct on factors that may affect the usage of the duty payer of Kuala Lumpur Branch to use the STAMPS online payment method. Findings revealed that relative advantage and compatibility are significant relationship towards the duty payers’ intention to use STAMPS online payment. Compatibility is the most significant determinant among the rest, while complexity is found not to have significant influenced on intention to use STAMPS online payment.The findings of this study could be used by IRBM to understand the behaviour of the targeted user of STAMPS. By understanding the factors, IRBM can plan the right strategy to promote the STAMPS by the users which in return will be beneficial in time and cost savings. It can also be useful to other government agencies that provide online services to employers. This study adds to current literature on intention to use technology from the organisation perspective

La inteligencia de negocios y la analítica de datos en los procesos empresariales

Business intelligence and data analytics in business processes are applied in several organizational sectors, the latter represents a competitive advantage factor, for this purpose it is necessary to use technological tools and to define the processes that allow generating mature management models, while business intelligence and data analytics represent, as a business strategy, an important factor in performance and decision-making. The objective was to establish a theoretical framework of business intelligence and data analytics in business processes, in this article journal, articles indexed in SCOPUS, Web of Science and Scielo were reviewed through the use of academic google, the review range was between 2017 and 2021. The results revealed that the business intelligence and data analytics solutions are most frequently applied in the business sector and empirical methodology is moreover the most widely applied. It was concluded that this study constitutes a theoretical framework for future research on business intelligence and data analytics in business processes.La inteligencia de negocios y la analítica de datos en los procesos empresariales se aplican en varios sectores organizacionales, este último representa un factor de ventaja competitiva, para este fin es necesario utilizar herramientas tecnológicas y definir los procesos que permitan generar modelos maduros de gestión, mientras que la inteligencia de negocios y la analítica de datos representan, como estrategia empresarial, es un factor importante de rendimiento y toma de decisiones. El objetivo fue establecer un marco de referencia teórica de la inteligencia de negocios y la analítica de datos en los procesos empresariales, en este artículo se revisaron artículos de revista indizadas en SCOPUS, Web of Science y Scielo a través del uso de google académico, el rango de revisión fue entre los años 2017 y 2021. Los resultados revelaron que el sector empresarial es donde se aplican con mayor frecuencia las soluciones en inteligencia de negocios y analítica de datos, además la metodología empírica es la más aplicada. Se concluyó que este estudio constituye un marco de referencia teórica para futuras investigaciones sobre la inteligencia de negocios y la analítica de datos en los procesos empresariales

A conceptual model of business intelligence system adoption for the textile and apparel industry in Pakistan

Textile and Apparel (T&A) industry is the backbone of Pakistani economy, including one-fourth of the industrial sector, and comprises 40% of industrial employees and approximately 60% share of Pakistani exports. Although, industry is striving hard to compete in international market; a persistent stream of innovation is required to maintain its due share in recent quota free global trade of textiles. Business Intelligence (BI) system is one of the most-used buzzwords in the modern business landscape for well informed decision making. In spite of the great synergies and benefits, BI system grant to the businesses and organizations. The adoption level is low with high failure ratio, especially in developing countries. Further, researchers did not propose any theory or model for the T & A industry. This study aims to fill this gap by conducting a Systematic Literature Review (SLR) for identifying the most appropriate factors, theory and model for the current study. Total of 75 studies were selected which were published during the period of 2011- 2020. A conceptual model is developed with most potential factors by using Technology-OrganizationEnvironment (TOE) framework. This conceptual model will guide the policy makers and industry practitioners to integrate and adopt the BI system successfully that would helpful to achieve competitive edge in the international business markets

Relationship of data analytics in the productivity and growth of organizations

Cada vez son más las organizaciones a nivel mundial que entienden la importancia de manejar de forma eficaz la información tanto interna como externa que se produce y genera en torno a la cadena de valor de sus operaciones. Sin embargo, aún son muchos los desafíos de esta disciplina en Latinoamérica, como es el caso de Colombia, teniendo en cuenta que se ha venido aplicando más desde su enfoque descriptivo que el predictivo; dejando así de aprovechar métodos y técnicas que le permitirían alcanzar una ventaja competitiva. Siendo el objetivo general de este análisis establecer la relación que existe entre la Analítica de Datos en la productividad y crecimiento de las organizaciones. Para ello se asumió un estudio cualitativo, bajo un diseño documental exhaustivo, con referentes de bases reconocidas, a través del cual se logró no solo definir cuáles son los beneficios de su implementación en cualquier tipo de empresa u organización, sino a su vez, visualizar el panorama o escenario futuro que se presenta en la transformación digital y los avances tecnológicos para el desarrollo de la economía global. Dejando claro que la relación de la Analítica de Datos en la productividad y crecimiento de las organizaciones se encuentra en su capacidad de predecir o anticiparse a los cambios de las economías mundiales, adaptándose con facilidad y eficiencia a los nuevos procesos, que terminan siendo en su mayoría, digitalizados sobre una plataforma 4.0. Capitalizando de esta forma su mayor recurso “el Talento Humano”, quienes han de manejar de forma eficaz los datos y propiciar con ello la toma efectiva de decisiones.Universidad Libre Seccional Cúcuta - Facultad de Ingenierías -- Ingeniería en Tecnología de la Información y las ComunicacionesMore and more organizations worldwide understand the importance of effectively managing both internal and external information that is produced and generated around the value chain of their operations. However, there are still many challenges of this discipline in Latin Relación de la Analítica de Datos en la productividad y crecimiento de las organizaciones Relationship of Data Analytics in the productivity and growth of organizations America, as is the case of Colombia, taking into account that it has been applied more from its descriptive approach than the predictive one; thus ceasing to take advantage of methods and techniques that would allow it to achieve a competitive advantage. Being the general objective of this analysis to establish the relationship that exists between Data Analytics in the productivity and growth of organizations. For this, a qualitative study was assumed, under an exhaustive documentary design, with references from recognized bases, through which it was possible not only to define the benefits of its implementation in any type of company or organization, but also to visualize the panorama or future scenario that is presented in the digital transformation and technological advances for the development of the global economy. Making it clear that the relationship of Data Analytics in the productivity and growth of organizations is found in its ability to predict or anticipate changes in world economies, easily and efficiently adapting to new processes, which end up being in their majority, digitized on a 4.0 platform. Capitalizing in this way its greatest resource "Human Talent", who have to effectively manage the data and thereby promote effective decision making

Provide management dashboard design framework, application of QFD in intelligent business systems

Dashboards are an important tool for monitoring the performance of the organization and the decisions of managers, so their proper design in an integrated and orderly manner, taking into account the needs of customers and users and in accordance with organizational goals, is essential. The purpose of this study is to provide a framework for designing management dashboards with QFD approach. For this purpose, after in-depth study in literature review, a conceptual research model was proposed, then using a mixed exploratory research Approach, management dashboard design framework, was presented. The statistical population of the qualitative section included 40 articles out of 452 articles related to the period 2005 to 2020 and related to dashboard topics and its design, which was done by Meta-Synthesizing method. Also, in quantitative part of the research, in order to validate the proposed framework and screen the indicators, fuzzy Delphi technique was used. The statistical population at this stage was 18 managers in different fields and 12 IT specialists and thus the framework. The design of management dashboards consisted of 4 dimensions, 11 components and 102 final indicators

Inteligencia de negocios aplicado al proceso de toma de decisiones en el área TI del Hospital de Lima Norte, 2022

El presente trabajo tuvo como objetivo determinar la influencia de la Inteligencia de Negocios aplicado al proceso de la toma de decisiones en el área de TI del Hospital de Lima Norte con la finalidad de dotar al establecimiento de Salud con las herramientas necesarias para una acertada toma de decisiones. La investigación fue realizada bajo la metodología de tipo aplicada con un enfoque cuantitativo y con un diseño pre experimental, utilizando como la técnica la observación; la población y muestra estuvo conformada por 100 registros, además de ello se utilizó el método hipotético deductivo. El resultado de la investigación logro determinar la inteligencia de negocios tiene un efecto positivo para la disponibilidad de la información pues logro alcanzar un 97% de disponibilidad, asimismo se obtuvo un 89% de mejoría en cuanto a la eficiencia con la entrega de reportes a tiempo y 97% de mejoría en la eficacia con respecto al cumplimiento de los registros ejecutados

Out of the way, human! Understanding post-adoption of last-mile delivery robots

The pace of technological development is exceeding expectations and transforming the landscape of last-mile delivery. This study investigates how users' post-adoption behavior in using delivery robots is formed. Based on the task-technology fit (TTF) model, we present a research model that includes both direct and indirect factors that have been previously overlooked in the literature. We collected data from 550 users of delivery robots. Our structural equation modelling results show that two hedonic- (i.e., gratification and anthropomorphism) and three utilitarian- (i.e., service quality experience, delivery task requirements, and user-facing technology performance) driven factors predict perceived TTF in using delivery robots. Value-in-use and trust have sequential mediating effects that connect perceived TTF and service reuse likelihood and word-of-mouth recommendation. Our findings suggest ways to improve last-mile delivery robot strategies and provide practical implications for the industry